{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import uproot\t\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import colormaps\n",
    "from mpl_toolkits import mplot3d\n",
    "import awkward as ak\n",
    "from scipy.optimize import curve_fit\n",
    "from scipy import stats\n",
    "from methods.fit_linear_regression_model import fit_linear_regression_model\n",
    "import sklearn\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def round(n, k):\n",
    "    # function to round number 'n' up/down to nearest 'k'\n",
    "    # use positive k to round up\n",
    "    # use negative k to round down\n",
    "\n",
    "    return n - n % k"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "41978 8523\n",
      "49865\n"
     ]
    }
   ],
   "source": [
    "file = uproot.open(\n",
    "    \"tracking_losses_ntuple_B_rad_length_beginVelo2endVelo.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n",
    ")\n",
    "\n",
    "# selektiere nur elektronen von B->K*ee\n",
    "allcolumns = file.arrays()\n",
    "found = allcolumns[(allcolumns.isElectron) & (~allcolumns.lost) & (allcolumns.fromB)]\n",
    "lost = allcolumns[(allcolumns.isElectron) & (allcolumns.lost) & (allcolumns.fromB)]\n",
    "\n",
    "electrons = allcolumns[\n",
    "    (allcolumns.isElectron)\n",
    "    & (allcolumns.fromB)\n",
    "    & (allcolumns.eta <= 5.0)\n",
    "    & (allcolumns.eta >= 1.5)\n",
    "    & (np.abs(allcolumns.phi) < 3.142)\n",
    "]\n",
    "\n",
    "print(ak.num(found, axis=0), ak.num(lost, axis=0))\n",
    "print(ak.num(electrons, axis=0))\n",
    "# ak.count(found, axis=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# variables\n",
    "\n",
    "eta_a = ak.to_numpy(electrons[\"eta\"])\n",
    "phi_a = ak.to_numpy(electrons[\"phi\"])\n",
    "rad_length_frac_a = ak.to_numpy(electrons[\"rad_length_frac\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(\n",
    "    rad_length_frac_a,\n",
    "    bins=100,\n",
    "    density=True,\n",
    "    alpha=0.5,\n",
    "    color=\"blue\",\n",
    "    histtype=\"bar\",\n",
    "    range=[0, 1],\n",
    ")\n",
    "plt.xlim(0, 1)\n",
    "# plt.yscale(\"log\")\n",
    "plt.title(\"radiation length fraction beginVelo2endVelo\")\n",
    "plt.xlabel(f\"$x/X_0$\")\n",
    "plt.ylabel(\"a.u.\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame({\n",
    "    \"phi\": phi_a * 90.0 / np.pi,\n",
    "    \"eta\": eta_a,\n",
    "    \"rad_length_frac\": rad_length_frac_a,\n",
    "})\n",
    "df = df.round({\"phi\": 0, \"eta\": 1, \"rad_length_frac\": 4})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_pivoted = df.pivot_table(\n",
    "    index=\"eta\",\n",
    "    columns=\"phi\",\n",
    "    values=\"rad_length_frac\",\n",
    "    margins=False,\n",
    "    fill_value=0,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>phi</th>\n",
       "      <th>-90.0</th>\n",
       "      <th>-89.0</th>\n",
       "      <th>-88.0</th>\n",
       "      <th>-87.0</th>\n",
       "      <th>-86.0</th>\n",
       "      <th>-85.0</th>\n",
       "      <th>-84.0</th>\n",
       "      <th>-83.0</th>\n",
       "      <th>-82.0</th>\n",
       "      <th>-81.0</th>\n",
       "      <th>...</th>\n",
       "      <th>81.0</th>\n",
       "      <th>82.0</th>\n",
       "      <th>83.0</th>\n",
       "      <th>84.0</th>\n",
       "      <th>85.0</th>\n",
       "      <th>86.0</th>\n",
       "      <th>87.0</th>\n",
       "      <th>88.0</th>\n",
       "      <th>89.0</th>\n",
       "      <th>90.0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>eta</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1.5</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.6</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.355900</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.526900</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.7</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.253200</td>\n",
       "      <td>0.378900</td>\n",
       "      <td>0.459800</td>\n",
       "      <td>0.169100</td>\n",
       "      <td>0.179750</td>\n",
       "      <td>0.187200</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.228125</td>\n",
       "      <td>0.177800</td>\n",
       "      <td>...</td>\n",
       "      <td>0.124700</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.140200</td>\n",
       "      <td>0.177500</td>\n",
       "      <td>0.475900</td>\n",
       "      <td>0.275300</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.244850</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.8</th>\n",
       "      <td>0.141700</td>\n",
       "      <td>0.420150</td>\n",
       "      <td>0.311400</td>\n",
       "      <td>0.370620</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.162100</td>\n",
       "      <td>0.186800</td>\n",
       "      <td>0.159033</td>\n",
       "      <td>0.121133</td>\n",
       "      <td>0.222767</td>\n",
       "      <td>...</td>\n",
       "      <td>0.159050</td>\n",
       "      <td>0.128229</td>\n",
       "      <td>0.148540</td>\n",
       "      <td>0.147600</td>\n",
       "      <td>0.213700</td>\n",
       "      <td>0.396150</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.417850</td>\n",
       "      <td>0.216000</td>\n",
       "      <td>0.116000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.9</th>\n",
       "      <td>0.135300</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.164100</td>\n",
       "      <td>0.388667</td>\n",
       "      <td>0.399800</td>\n",
       "      <td>0.243000</td>\n",
       "      <td>0.165000</td>\n",
       "      <td>0.143320</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.157660</td>\n",
       "      <td>0.189700</td>\n",
       "      <td>0.159575</td>\n",
       "      <td>0.180275</td>\n",
       "      <td>0.193267</td>\n",
       "      <td>0.321533</td>\n",
       "      <td>0.484200</td>\n",
       "      <td>0.376680</td>\n",
       "      <td>0.431967</td>\n",
       "      <td>0.368800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.0</th>\n",
       "      <td>0.353400</td>\n",
       "      <td>0.308690</td>\n",
       "      <td>0.303800</td>\n",
       "      <td>0.396450</td>\n",
       "      <td>0.436400</td>\n",
       "      <td>0.269900</td>\n",
       "      <td>0.170950</td>\n",
       "      <td>0.177560</td>\n",
       "      <td>0.151720</td>\n",
       "      <td>0.162122</td>\n",
       "      <td>...</td>\n",
       "      <td>0.152460</td>\n",
       "      <td>0.158525</td>\n",
       "      <td>0.185100</td>\n",
       "      <td>0.173757</td>\n",
       "      <td>0.251557</td>\n",
       "      <td>0.274000</td>\n",
       "      <td>0.420800</td>\n",
       "      <td>0.393471</td>\n",
       "      <td>0.451720</td>\n",
       "      <td>0.210150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.1</th>\n",
       "      <td>0.158200</td>\n",
       "      <td>0.232540</td>\n",
       "      <td>0.174500</td>\n",
       "      <td>0.259733</td>\n",
       "      <td>0.258775</td>\n",
       "      <td>0.205350</td>\n",
       "      <td>0.186400</td>\n",
       "      <td>0.167020</td>\n",
       "      <td>0.168629</td>\n",
       "      <td>0.163200</td>\n",
       "      <td>...</td>\n",
       "      <td>0.183743</td>\n",
       "      <td>0.185325</td>\n",
       "      <td>0.192740</td>\n",
       "      <td>0.239333</td>\n",
       "      <td>0.207709</td>\n",
       "      <td>0.304762</td>\n",
       "      <td>0.496100</td>\n",
       "      <td>0.302591</td>\n",
       "      <td>0.418425</td>\n",
       "      <td>0.300133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.2</th>\n",
       "      <td>0.220000</td>\n",
       "      <td>0.225210</td>\n",
       "      <td>0.355058</td>\n",
       "      <td>0.344350</td>\n",
       "      <td>0.291310</td>\n",
       "      <td>0.198650</td>\n",
       "      <td>0.197100</td>\n",
       "      <td>0.194667</td>\n",
       "      <td>0.158688</td>\n",
       "      <td>0.167200</td>\n",
       "      <td>...</td>\n",
       "      <td>0.179700</td>\n",
       "      <td>0.180930</td>\n",
       "      <td>0.190475</td>\n",
       "      <td>0.179700</td>\n",
       "      <td>0.197150</td>\n",
       "      <td>0.340950</td>\n",
       "      <td>0.189017</td>\n",
       "      <td>0.288957</td>\n",
       "      <td>0.287525</td>\n",
       "      <td>0.371600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.3</th>\n",
       "      <td>0.338300</td>\n",
       "      <td>0.249837</td>\n",
       "      <td>0.300908</td>\n",
       "      <td>0.230829</td>\n",
       "      <td>0.376617</td>\n",
       "      <td>0.163367</td>\n",
       "      <td>0.192200</td>\n",
       "      <td>0.163618</td>\n",
       "      <td>0.150042</td>\n",
       "      <td>0.178250</td>\n",
       "      <td>...</td>\n",
       "      <td>0.181967</td>\n",
       "      <td>0.188125</td>\n",
       "      <td>0.184033</td>\n",
       "      <td>0.213550</td>\n",
       "      <td>0.218757</td>\n",
       "      <td>0.164600</td>\n",
       "      <td>0.316006</td>\n",
       "      <td>0.378400</td>\n",
       "      <td>0.296345</td>\n",
       "      <td>0.267340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.4</th>\n",
       "      <td>0.299714</td>\n",
       "      <td>0.245888</td>\n",
       "      <td>0.354560</td>\n",
       "      <td>0.263557</td>\n",
       "      <td>0.330100</td>\n",
       "      <td>0.240408</td>\n",
       "      <td>0.202240</td>\n",
       "      <td>0.182417</td>\n",
       "      <td>0.175910</td>\n",
       "      <td>0.164650</td>\n",
       "      <td>...</td>\n",
       "      <td>0.182113</td>\n",
       "      <td>0.200911</td>\n",
       "      <td>0.197689</td>\n",
       "      <td>0.209911</td>\n",
       "      <td>0.300017</td>\n",
       "      <td>0.327933</td>\n",
       "      <td>0.281250</td>\n",
       "      <td>0.398044</td>\n",
       "      <td>0.257986</td>\n",
       "      <td>0.277720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.5</th>\n",
       "      <td>0.220817</td>\n",
       "      <td>0.310787</td>\n",
       "      <td>0.407230</td>\n",
       "      <td>0.271920</td>\n",
       "      <td>0.355700</td>\n",
       "      <td>0.243955</td>\n",
       "      <td>0.222678</td>\n",
       "      <td>0.227625</td>\n",
       "      <td>0.181771</td>\n",
       "      <td>0.177013</td>\n",
       "      <td>...</td>\n",
       "      <td>0.186971</td>\n",
       "      <td>0.210333</td>\n",
       "      <td>0.198900</td>\n",
       "      <td>0.233993</td>\n",
       "      <td>0.235725</td>\n",
       "      <td>0.309443</td>\n",
       "      <td>0.324073</td>\n",
       "      <td>0.338838</td>\n",
       "      <td>0.239044</td>\n",
       "      <td>0.244100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.6</th>\n",
       "      <td>0.289325</td>\n",
       "      <td>0.340494</td>\n",
       "      <td>0.396958</td>\n",
       "      <td>0.356700</td>\n",
       "      <td>0.326283</td>\n",
       "      <td>0.234962</td>\n",
       "      <td>0.207600</td>\n",
       "      <td>0.213810</td>\n",
       "      <td>0.189312</td>\n",
       "      <td>0.183936</td>\n",
       "      <td>...</td>\n",
       "      <td>0.202918</td>\n",
       "      <td>0.204109</td>\n",
       "      <td>0.231210</td>\n",
       "      <td>0.205230</td>\n",
       "      <td>0.258256</td>\n",
       "      <td>0.365645</td>\n",
       "      <td>0.380542</td>\n",
       "      <td>0.456878</td>\n",
       "      <td>0.311717</td>\n",
       "      <td>0.340000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.7</th>\n",
       "      <td>0.377340</td>\n",
       "      <td>0.309629</td>\n",
       "      <td>0.408500</td>\n",
       "      <td>0.395922</td>\n",
       "      <td>0.457153</td>\n",
       "      <td>0.245200</td>\n",
       "      <td>0.208144</td>\n",
       "      <td>0.227821</td>\n",
       "      <td>0.204533</td>\n",
       "      <td>0.200750</td>\n",
       "      <td>...</td>\n",
       "      <td>0.207200</td>\n",
       "      <td>0.206678</td>\n",
       "      <td>0.231667</td>\n",
       "      <td>0.214758</td>\n",
       "      <td>0.258890</td>\n",
       "      <td>0.398944</td>\n",
       "      <td>0.473256</td>\n",
       "      <td>0.495275</td>\n",
       "      <td>0.437533</td>\n",
       "      <td>0.433650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.8</th>\n",
       "      <td>0.406600</td>\n",
       "      <td>0.422255</td>\n",
       "      <td>0.336575</td>\n",
       "      <td>0.463889</td>\n",
       "      <td>0.405786</td>\n",
       "      <td>0.275860</td>\n",
       "      <td>0.226343</td>\n",
       "      <td>0.227864</td>\n",
       "      <td>0.228122</td>\n",
       "      <td>0.200971</td>\n",
       "      <td>...</td>\n",
       "      <td>0.212292</td>\n",
       "      <td>0.210667</td>\n",
       "      <td>0.233809</td>\n",
       "      <td>0.218453</td>\n",
       "      <td>0.285085</td>\n",
       "      <td>0.461650</td>\n",
       "      <td>0.429129</td>\n",
       "      <td>0.402710</td>\n",
       "      <td>0.501223</td>\n",
       "      <td>0.449325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.9</th>\n",
       "      <td>0.304183</td>\n",
       "      <td>0.299586</td>\n",
       "      <td>0.437578</td>\n",
       "      <td>0.310589</td>\n",
       "      <td>0.414592</td>\n",
       "      <td>0.250408</td>\n",
       "      <td>0.234600</td>\n",
       "      <td>0.220500</td>\n",
       "      <td>0.217856</td>\n",
       "      <td>0.228570</td>\n",
       "      <td>...</td>\n",
       "      <td>0.245578</td>\n",
       "      <td>0.240820</td>\n",
       "      <td>0.224706</td>\n",
       "      <td>0.230070</td>\n",
       "      <td>0.255575</td>\n",
       "      <td>0.248833</td>\n",
       "      <td>0.352486</td>\n",
       "      <td>0.193442</td>\n",
       "      <td>0.296429</td>\n",
       "      <td>0.450613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <td>0.177300</td>\n",
       "      <td>0.208607</td>\n",
       "      <td>0.246791</td>\n",
       "      <td>0.234960</td>\n",
       "      <td>0.247550</td>\n",
       "      <td>0.242510</td>\n",
       "      <td>0.243250</td>\n",
       "      <td>0.238464</td>\n",
       "      <td>0.220591</td>\n",
       "      <td>0.235342</td>\n",
       "      <td>...</td>\n",
       "      <td>0.242127</td>\n",
       "      <td>0.230633</td>\n",
       "      <td>0.234608</td>\n",
       "      <td>0.220050</td>\n",
       "      <td>0.246807</td>\n",
       "      <td>0.214400</td>\n",
       "      <td>0.207507</td>\n",
       "      <td>0.253059</td>\n",
       "      <td>0.225075</td>\n",
       "      <td>0.279833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.1</th>\n",
       "      <td>0.176850</td>\n",
       "      <td>0.174825</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.216220</td>\n",
       "      <td>0.238011</td>\n",
       "      <td>0.223344</td>\n",
       "      <td>0.236530</td>\n",
       "      <td>0.227418</td>\n",
       "      <td>0.238523</td>\n",
       "      <td>0.241125</td>\n",
       "      <td>...</td>\n",
       "      <td>0.234573</td>\n",
       "      <td>0.251121</td>\n",
       "      <td>0.221583</td>\n",
       "      <td>0.218742</td>\n",
       "      <td>0.230860</td>\n",
       "      <td>0.193880</td>\n",
       "      <td>0.212775</td>\n",
       "      <td>0.199833</td>\n",
       "      <td>0.201575</td>\n",
       "      <td>0.223025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.2</th>\n",
       "      <td>0.207217</td>\n",
       "      <td>0.190643</td>\n",
       "      <td>0.215775</td>\n",
       "      <td>0.195622</td>\n",
       "      <td>0.211843</td>\n",
       "      <td>0.222592</td>\n",
       "      <td>0.206457</td>\n",
       "      <td>0.208845</td>\n",
       "      <td>0.220572</td>\n",
       "      <td>0.213885</td>\n",
       "      <td>...</td>\n",
       "      <td>0.255383</td>\n",
       "      <td>0.226518</td>\n",
       "      <td>0.242144</td>\n",
       "      <td>0.234206</td>\n",
       "      <td>0.246940</td>\n",
       "      <td>0.251643</td>\n",
       "      <td>0.234863</td>\n",
       "      <td>0.194550</td>\n",
       "      <td>0.191622</td>\n",
       "      <td>0.224000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.3</th>\n",
       "      <td>0.212500</td>\n",
       "      <td>0.178411</td>\n",
       "      <td>0.200142</td>\n",
       "      <td>0.205387</td>\n",
       "      <td>0.247040</td>\n",
       "      <td>0.214215</td>\n",
       "      <td>0.205026</td>\n",
       "      <td>0.204368</td>\n",
       "      <td>0.234333</td>\n",
       "      <td>0.206138</td>\n",
       "      <td>...</td>\n",
       "      <td>0.242873</td>\n",
       "      <td>0.233411</td>\n",
       "      <td>0.231791</td>\n",
       "      <td>0.228750</td>\n",
       "      <td>0.225615</td>\n",
       "      <td>0.243327</td>\n",
       "      <td>0.239650</td>\n",
       "      <td>0.197650</td>\n",
       "      <td>0.220333</td>\n",
       "      <td>0.227175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.4</th>\n",
       "      <td>0.203900</td>\n",
       "      <td>0.229470</td>\n",
       "      <td>0.212793</td>\n",
       "      <td>0.225382</td>\n",
       "      <td>0.197680</td>\n",
       "      <td>0.207650</td>\n",
       "      <td>0.190145</td>\n",
       "      <td>0.184869</td>\n",
       "      <td>0.207871</td>\n",
       "      <td>0.206950</td>\n",
       "      <td>...</td>\n",
       "      <td>0.246590</td>\n",
       "      <td>0.192967</td>\n",
       "      <td>0.190444</td>\n",
       "      <td>0.211069</td>\n",
       "      <td>0.248655</td>\n",
       "      <td>0.218693</td>\n",
       "      <td>0.251355</td>\n",
       "      <td>0.221371</td>\n",
       "      <td>0.222414</td>\n",
       "      <td>0.201875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.5</th>\n",
       "      <td>0.209767</td>\n",
       "      <td>0.209209</td>\n",
       "      <td>0.214618</td>\n",
       "      <td>0.193182</td>\n",
       "      <td>0.223942</td>\n",
       "      <td>0.226656</td>\n",
       "      <td>0.224200</td>\n",
       "      <td>0.184867</td>\n",
       "      <td>0.235280</td>\n",
       "      <td>0.194992</td>\n",
       "      <td>...</td>\n",
       "      <td>0.231978</td>\n",
       "      <td>0.235050</td>\n",
       "      <td>0.226567</td>\n",
       "      <td>0.215307</td>\n",
       "      <td>0.216286</td>\n",
       "      <td>0.228554</td>\n",
       "      <td>0.227711</td>\n",
       "      <td>0.227467</td>\n",
       "      <td>0.241487</td>\n",
       "      <td>0.225700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.6</th>\n",
       "      <td>0.203100</td>\n",
       "      <td>0.199025</td>\n",
       "      <td>0.162311</td>\n",
       "      <td>0.218986</td>\n",
       "      <td>0.214600</td>\n",
       "      <td>0.202833</td>\n",
       "      <td>0.237267</td>\n",
       "      <td>0.190858</td>\n",
       "      <td>0.205893</td>\n",
       "      <td>0.208320</td>\n",
       "      <td>...</td>\n",
       "      <td>0.216200</td>\n",
       "      <td>0.196613</td>\n",
       "      <td>0.239618</td>\n",
       "      <td>0.216460</td>\n",
       "      <td>0.215436</td>\n",
       "      <td>0.214009</td>\n",
       "      <td>0.223700</td>\n",
       "      <td>0.205814</td>\n",
       "      <td>0.204694</td>\n",
       "      <td>0.224175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.7</th>\n",
       "      <td>0.254600</td>\n",
       "      <td>0.220037</td>\n",
       "      <td>0.224288</td>\n",
       "      <td>0.228317</td>\n",
       "      <td>0.203760</td>\n",
       "      <td>0.202433</td>\n",
       "      <td>0.130050</td>\n",
       "      <td>0.174056</td>\n",
       "      <td>0.218980</td>\n",
       "      <td>0.186362</td>\n",
       "      <td>...</td>\n",
       "      <td>0.199267</td>\n",
       "      <td>0.214478</td>\n",
       "      <td>0.197508</td>\n",
       "      <td>0.253433</td>\n",
       "      <td>0.221809</td>\n",
       "      <td>0.165333</td>\n",
       "      <td>0.235983</td>\n",
       "      <td>0.210500</td>\n",
       "      <td>0.209729</td>\n",
       "      <td>0.225800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.8</th>\n",
       "      <td>0.189386</td>\n",
       "      <td>0.212550</td>\n",
       "      <td>0.212787</td>\n",
       "      <td>0.218413</td>\n",
       "      <td>0.180314</td>\n",
       "      <td>0.182820</td>\n",
       "      <td>0.195475</td>\n",
       "      <td>0.191514</td>\n",
       "      <td>0.187533</td>\n",
       "      <td>0.206857</td>\n",
       "      <td>...</td>\n",
       "      <td>0.212150</td>\n",
       "      <td>0.189386</td>\n",
       "      <td>0.240175</td>\n",
       "      <td>0.226765</td>\n",
       "      <td>0.200056</td>\n",
       "      <td>0.213332</td>\n",
       "      <td>0.218785</td>\n",
       "      <td>0.229146</td>\n",
       "      <td>0.201712</td>\n",
       "      <td>0.208350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.9</th>\n",
       "      <td>0.152200</td>\n",
       "      <td>0.173320</td>\n",
       "      <td>0.202150</td>\n",
       "      <td>0.224311</td>\n",
       "      <td>0.203382</td>\n",
       "      <td>0.180042</td>\n",
       "      <td>0.179955</td>\n",
       "      <td>0.224317</td>\n",
       "      <td>0.201767</td>\n",
       "      <td>0.182942</td>\n",
       "      <td>...</td>\n",
       "      <td>0.217258</td>\n",
       "      <td>0.201900</td>\n",
       "      <td>0.195956</td>\n",
       "      <td>0.234673</td>\n",
       "      <td>0.187436</td>\n",
       "      <td>0.227500</td>\n",
       "      <td>0.218291</td>\n",
       "      <td>0.201937</td>\n",
       "      <td>0.212855</td>\n",
       "      <td>0.172500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>0.174950</td>\n",
       "      <td>0.188591</td>\n",
       "      <td>0.202700</td>\n",
       "      <td>0.200275</td>\n",
       "      <td>0.226100</td>\n",
       "      <td>0.202900</td>\n",
       "      <td>0.208282</td>\n",
       "      <td>0.218286</td>\n",
       "      <td>0.244600</td>\n",
       "      <td>0.171700</td>\n",
       "      <td>...</td>\n",
       "      <td>0.175250</td>\n",
       "      <td>0.243971</td>\n",
       "      <td>0.205017</td>\n",
       "      <td>0.199178</td>\n",
       "      <td>0.194200</td>\n",
       "      <td>0.166775</td>\n",
       "      <td>0.186650</td>\n",
       "      <td>0.200456</td>\n",
       "      <td>0.179150</td>\n",
       "      <td>0.193475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.1</th>\n",
       "      <td>0.188150</td>\n",
       "      <td>0.182111</td>\n",
       "      <td>0.192187</td>\n",
       "      <td>0.182120</td>\n",
       "      <td>0.160708</td>\n",
       "      <td>0.180787</td>\n",
       "      <td>0.218877</td>\n",
       "      <td>0.195705</td>\n",
       "      <td>0.173257</td>\n",
       "      <td>0.224460</td>\n",
       "      <td>...</td>\n",
       "      <td>0.199680</td>\n",
       "      <td>0.186400</td>\n",
       "      <td>0.223425</td>\n",
       "      <td>0.223700</td>\n",
       "      <td>0.198700</td>\n",
       "      <td>0.211793</td>\n",
       "      <td>0.210700</td>\n",
       "      <td>0.168300</td>\n",
       "      <td>0.200883</td>\n",
       "      <td>0.202600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.2</th>\n",
       "      <td>0.204350</td>\n",
       "      <td>0.204967</td>\n",
       "      <td>0.157154</td>\n",
       "      <td>0.230100</td>\n",
       "      <td>0.194117</td>\n",
       "      <td>0.193585</td>\n",
       "      <td>0.167480</td>\n",
       "      <td>0.154408</td>\n",
       "      <td>0.174150</td>\n",
       "      <td>0.241283</td>\n",
       "      <td>...</td>\n",
       "      <td>0.134962</td>\n",
       "      <td>0.201320</td>\n",
       "      <td>0.212757</td>\n",
       "      <td>0.143350</td>\n",
       "      <td>0.162450</td>\n",
       "      <td>0.185694</td>\n",
       "      <td>0.196530</td>\n",
       "      <td>0.181363</td>\n",
       "      <td>0.124100</td>\n",
       "      <td>0.154300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.3</th>\n",
       "      <td>0.111900</td>\n",
       "      <td>0.163650</td>\n",
       "      <td>0.242429</td>\n",
       "      <td>0.170043</td>\n",
       "      <td>0.233867</td>\n",
       "      <td>0.242429</td>\n",
       "      <td>0.106900</td>\n",
       "      <td>0.234722</td>\n",
       "      <td>0.199713</td>\n",
       "      <td>0.170850</td>\n",
       "      <td>...</td>\n",
       "      <td>0.199612</td>\n",
       "      <td>0.204267</td>\n",
       "      <td>0.162320</td>\n",
       "      <td>0.177400</td>\n",
       "      <td>0.182486</td>\n",
       "      <td>0.168967</td>\n",
       "      <td>0.240900</td>\n",
       "      <td>0.198540</td>\n",
       "      <td>0.211260</td>\n",
       "      <td>0.154700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.4</th>\n",
       "      <td>0.065600</td>\n",
       "      <td>0.179157</td>\n",
       "      <td>0.210950</td>\n",
       "      <td>0.198383</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.248883</td>\n",
       "      <td>0.156400</td>\n",
       "      <td>0.232300</td>\n",
       "      <td>0.203975</td>\n",
       "      <td>0.224718</td>\n",
       "      <td>...</td>\n",
       "      <td>0.256600</td>\n",
       "      <td>0.106900</td>\n",
       "      <td>0.213975</td>\n",
       "      <td>0.193763</td>\n",
       "      <td>0.180425</td>\n",
       "      <td>0.098260</td>\n",
       "      <td>0.176700</td>\n",
       "      <td>0.130213</td>\n",
       "      <td>0.205100</td>\n",
       "      <td>0.233800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.5</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.193960</td>\n",
       "      <td>0.220067</td>\n",
       "      <td>0.188533</td>\n",
       "      <td>0.244800</td>\n",
       "      <td>0.140017</td>\n",
       "      <td>0.218725</td>\n",
       "      <td>0.214050</td>\n",
       "      <td>0.199425</td>\n",
       "      <td>0.169800</td>\n",
       "      <td>...</td>\n",
       "      <td>0.237283</td>\n",
       "      <td>0.173557</td>\n",
       "      <td>0.187260</td>\n",
       "      <td>0.238050</td>\n",
       "      <td>0.184175</td>\n",
       "      <td>0.165300</td>\n",
       "      <td>0.247133</td>\n",
       "      <td>0.185775</td>\n",
       "      <td>0.235250</td>\n",
       "      <td>0.209500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.6</th>\n",
       "      <td>0.229400</td>\n",
       "      <td>0.155000</td>\n",
       "      <td>0.116629</td>\n",
       "      <td>0.205517</td>\n",
       "      <td>0.221433</td>\n",
       "      <td>0.203664</td>\n",
       "      <td>0.148467</td>\n",
       "      <td>0.273050</td>\n",
       "      <td>0.160400</td>\n",
       "      <td>0.176225</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.178225</td>\n",
       "      <td>0.225750</td>\n",
       "      <td>0.185767</td>\n",
       "      <td>0.120300</td>\n",
       "      <td>0.137700</td>\n",
       "      <td>0.137350</td>\n",
       "      <td>0.183275</td>\n",
       "      <td>0.197100</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.7</th>\n",
       "      <td>0.184300</td>\n",
       "      <td>0.232700</td>\n",
       "      <td>0.159950</td>\n",
       "      <td>0.144400</td>\n",
       "      <td>0.161300</td>\n",
       "      <td>0.134360</td>\n",
       "      <td>0.206125</td>\n",
       "      <td>0.149975</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.186340</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.059500</td>\n",
       "      <td>0.165750</td>\n",
       "      <td>0.237600</td>\n",
       "      <td>0.190820</td>\n",
       "      <td>0.058800</td>\n",
       "      <td>0.225250</td>\n",
       "      <td>0.261800</td>\n",
       "      <td>0.103200</td>\n",
       "      <td>0.075550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.8</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.107667</td>\n",
       "      <td>0.096550</td>\n",
       "      <td>0.181325</td>\n",
       "      <td>0.161300</td>\n",
       "      <td>0.281700</td>\n",
       "      <td>0.250350</td>\n",
       "      <td>0.105450</td>\n",
       "      <td>0.133400</td>\n",
       "      <td>0.189200</td>\n",
       "      <td>...</td>\n",
       "      <td>0.199300</td>\n",
       "      <td>0.069200</td>\n",
       "      <td>0.282200</td>\n",
       "      <td>0.265200</td>\n",
       "      <td>0.163650</td>\n",
       "      <td>0.075500</td>\n",
       "      <td>0.108400</td>\n",
       "      <td>0.202933</td>\n",
       "      <td>0.067500</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.9</th>\n",
       "      <td>0.078100</td>\n",
       "      <td>0.099600</td>\n",
       "      <td>0.086867</td>\n",
       "      <td>0.078340</td>\n",
       "      <td>0.077900</td>\n",
       "      <td>0.089733</td>\n",
       "      <td>0.080800</td>\n",
       "      <td>0.141067</td>\n",
       "      <td>0.153975</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.123550</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.135033</td>\n",
       "      <td>0.195800</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.082100</td>\n",
       "      <td>0.072100</td>\n",
       "      <td>0.078550</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5.0</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.075250</td>\n",
       "      <td>0.067500</td>\n",
       "      <td>0.070600</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.057800</td>\n",
       "      <td>0.326000</td>\n",
       "      <td>0.074800</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.072700</td>\n",
       "      <td>0.078500</td>\n",
       "      <td>0.072767</td>\n",
       "      <td>0.030700</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.084400</td>\n",
       "      <td>0.070900</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>36 rows × 181 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "phi     -90.0     -89.0     -88.0     -87.0     -86.0     -85.0     -84.0  \\\n",
       "eta                                                                         \n",
       "1.5  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "1.6  0.000000  0.355900  0.000000  0.526900  0.000000  0.000000  0.000000   \n",
       "1.7  0.000000  0.253200  0.378900  0.459800  0.169100  0.179750  0.187200   \n",
       "1.8  0.141700  0.420150  0.311400  0.370620  0.000000  0.162100  0.186800   \n",
       "1.9  0.135300  0.000000  0.164100  0.388667  0.399800  0.243000  0.165000   \n",
       "2.0  0.353400  0.308690  0.303800  0.396450  0.436400  0.269900  0.170950   \n",
       "2.1  0.158200  0.232540  0.174500  0.259733  0.258775  0.205350  0.186400   \n",
       "2.2  0.220000  0.225210  0.355058  0.344350  0.291310  0.198650  0.197100   \n",
       "2.3  0.338300  0.249837  0.300908  0.230829  0.376617  0.163367  0.192200   \n",
       "2.4  0.299714  0.245888  0.354560  0.263557  0.330100  0.240408  0.202240   \n",
       "2.5  0.220817  0.310787  0.407230  0.271920  0.355700  0.243955  0.222678   \n",
       "2.6  0.289325  0.340494  0.396958  0.356700  0.326283  0.234962  0.207600   \n",
       "2.7  0.377340  0.309629  0.408500  0.395922  0.457153  0.245200  0.208144   \n",
       "2.8  0.406600  0.422255  0.336575  0.463889  0.405786  0.275860  0.226343   \n",
       "2.9  0.304183  0.299586  0.437578  0.310589  0.414592  0.250408  0.234600   \n",
       "3.0  0.177300  0.208607  0.246791  0.234960  0.247550  0.242510  0.243250   \n",
       "3.1  0.176850  0.174825  0.200000  0.216220  0.238011  0.223344  0.236530   \n",
       "3.2  0.207217  0.190643  0.215775  0.195622  0.211843  0.222592  0.206457   \n",
       "3.3  0.212500  0.178411  0.200142  0.205387  0.247040  0.214215  0.205026   \n",
       "3.4  0.203900  0.229470  0.212793  0.225382  0.197680  0.207650  0.190145   \n",
       "3.5  0.209767  0.209209  0.214618  0.193182  0.223942  0.226656  0.224200   \n",
       "3.6  0.203100  0.199025  0.162311  0.218986  0.214600  0.202833  0.237267   \n",
       "3.7  0.254600  0.220037  0.224288  0.228317  0.203760  0.202433  0.130050   \n",
       "3.8  0.189386  0.212550  0.212787  0.218413  0.180314  0.182820  0.195475   \n",
       "3.9  0.152200  0.173320  0.202150  0.224311  0.203382  0.180042  0.179955   \n",
       "4.0  0.174950  0.188591  0.202700  0.200275  0.226100  0.202900  0.208282   \n",
       "4.1  0.188150  0.182111  0.192187  0.182120  0.160708  0.180787  0.218877   \n",
       "4.2  0.204350  0.204967  0.157154  0.230100  0.194117  0.193585  0.167480   \n",
       "4.3  0.111900  0.163650  0.242429  0.170043  0.233867  0.242429  0.106900   \n",
       "4.4  0.065600  0.179157  0.210950  0.198383  0.000000  0.248883  0.156400   \n",
       "4.5  0.000000  0.193960  0.220067  0.188533  0.244800  0.140017  0.218725   \n",
       "4.6  0.229400  0.155000  0.116629  0.205517  0.221433  0.203664  0.148467   \n",
       "4.7  0.184300  0.232700  0.159950  0.144400  0.161300  0.134360  0.206125   \n",
       "4.8  0.000000  0.107667  0.096550  0.181325  0.161300  0.281700  0.250350   \n",
       "4.9  0.078100  0.099600  0.086867  0.078340  0.077900  0.089733  0.080800   \n",
       "5.0  0.000000  0.075250  0.067500  0.070600  0.000000  0.057800  0.326000   \n",
       "\n",
       "phi     -83.0     -82.0     -81.0  ...      81.0      82.0      83.0  \\\n",
       "eta                                ...                                 \n",
       "1.5  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "1.6  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "1.7  0.000000  0.228125  0.177800  ...  0.124700  0.000000  0.000000   \n",
       "1.8  0.159033  0.121133  0.222767  ...  0.159050  0.128229  0.148540   \n",
       "1.9  0.143320  0.200000  0.000000  ...  0.157660  0.189700  0.159575   \n",
       "2.0  0.177560  0.151720  0.162122  ...  0.152460  0.158525  0.185100   \n",
       "2.1  0.167020  0.168629  0.163200  ...  0.183743  0.185325  0.192740   \n",
       "2.2  0.194667  0.158688  0.167200  ...  0.179700  0.180930  0.190475   \n",
       "2.3  0.163618  0.150042  0.178250  ...  0.181967  0.188125  0.184033   \n",
       "2.4  0.182417  0.175910  0.164650  ...  0.182113  0.200911  0.197689   \n",
       "2.5  0.227625  0.181771  0.177013  ...  0.186971  0.210333  0.198900   \n",
       "2.6  0.213810  0.189312  0.183936  ...  0.202918  0.204109  0.231210   \n",
       "2.7  0.227821  0.204533  0.200750  ...  0.207200  0.206678  0.231667   \n",
       "2.8  0.227864  0.228122  0.200971  ...  0.212292  0.210667  0.233809   \n",
       "2.9  0.220500  0.217856  0.228570  ...  0.245578  0.240820  0.224706   \n",
       "3.0  0.238464  0.220591  0.235342  ...  0.242127  0.230633  0.234608   \n",
       "3.1  0.227418  0.238523  0.241125  ...  0.234573  0.251121  0.221583   \n",
       "3.2  0.208845  0.220572  0.213885  ...  0.255383  0.226518  0.242144   \n",
       "3.3  0.204368  0.234333  0.206138  ...  0.242873  0.233411  0.231791   \n",
       "3.4  0.184869  0.207871  0.206950  ...  0.246590  0.192967  0.190444   \n",
       "3.5  0.184867  0.235280  0.194992  ...  0.231978  0.235050  0.226567   \n",
       "3.6  0.190858  0.205893  0.208320  ...  0.216200  0.196613  0.239618   \n",
       "3.7  0.174056  0.218980  0.186362  ...  0.199267  0.214478  0.197508   \n",
       "3.8  0.191514  0.187533  0.206857  ...  0.212150  0.189386  0.240175   \n",
       "3.9  0.224317  0.201767  0.182942  ...  0.217258  0.201900  0.195956   \n",
       "4.0  0.218286  0.244600  0.171700  ...  0.175250  0.243971  0.205017   \n",
       "4.1  0.195705  0.173257  0.224460  ...  0.199680  0.186400  0.223425   \n",
       "4.2  0.154408  0.174150  0.241283  ...  0.134962  0.201320  0.212757   \n",
       "4.3  0.234722  0.199713  0.170850  ...  0.199612  0.204267  0.162320   \n",
       "4.4  0.232300  0.203975  0.224718  ...  0.256600  0.106900  0.213975   \n",
       "4.5  0.214050  0.199425  0.169800  ...  0.237283  0.173557  0.187260   \n",
       "4.6  0.273050  0.160400  0.176225  ...  0.000000  0.178225  0.225750   \n",
       "4.7  0.149975  0.000000  0.186340  ...  0.000000  0.059500  0.165750   \n",
       "4.8  0.105450  0.133400  0.189200  ...  0.199300  0.069200  0.282200   \n",
       "4.9  0.141067  0.153975  0.000000  ...  0.000000  0.123550  0.000000   \n",
       "5.0  0.074800  0.000000  0.000000  ...  0.072700  0.078500  0.072767   \n",
       "\n",
       "phi      84.0      85.0      86.0      87.0      88.0      89.0      90.0  \n",
       "eta                                                                        \n",
       "1.5  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  \n",
       "1.6  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  \n",
       "1.7  0.140200  0.177500  0.475900  0.275300  0.000000  0.244850  0.000000  \n",
       "1.8  0.147600  0.213700  0.396150  0.000000  0.417850  0.216000  0.116000  \n",
       "1.9  0.180275  0.193267  0.321533  0.484200  0.376680  0.431967  0.368800  \n",
       "2.0  0.173757  0.251557  0.274000  0.420800  0.393471  0.451720  0.210150  \n",
       "2.1  0.239333  0.207709  0.304762  0.496100  0.302591  0.418425  0.300133  \n",
       "2.2  0.179700  0.197150  0.340950  0.189017  0.288957  0.287525  0.371600  \n",
       "2.3  0.213550  0.218757  0.164600  0.316006  0.378400  0.296345  0.267340  \n",
       "2.4  0.209911  0.300017  0.327933  0.281250  0.398044  0.257986  0.277720  \n",
       "2.5  0.233993  0.235725  0.309443  0.324073  0.338838  0.239044  0.244100  \n",
       "2.6  0.205230  0.258256  0.365645  0.380542  0.456878  0.311717  0.340000  \n",
       "2.7  0.214758  0.258890  0.398944  0.473256  0.495275  0.437533  0.433650  \n",
       "2.8  0.218453  0.285085  0.461650  0.429129  0.402710  0.501223  0.449325  \n",
       "2.9  0.230070  0.255575  0.248833  0.352486  0.193442  0.296429  0.450613  \n",
       "3.0  0.220050  0.246807  0.214400  0.207507  0.253059  0.225075  0.279833  \n",
       "3.1  0.218742  0.230860  0.193880  0.212775  0.199833  0.201575  0.223025  \n",
       "3.2  0.234206  0.246940  0.251643  0.234863  0.194550  0.191622  0.224000  \n",
       "3.3  0.228750  0.225615  0.243327  0.239650  0.197650  0.220333  0.227175  \n",
       "3.4  0.211069  0.248655  0.218693  0.251355  0.221371  0.222414  0.201875  \n",
       "3.5  0.215307  0.216286  0.228554  0.227711  0.227467  0.241487  0.225700  \n",
       "3.6  0.216460  0.215436  0.214009  0.223700  0.205814  0.204694  0.224175  \n",
       "3.7  0.253433  0.221809  0.165333  0.235983  0.210500  0.209729  0.225800  \n",
       "3.8  0.226765  0.200056  0.213332  0.218785  0.229146  0.201712  0.208350  \n",
       "3.9  0.234673  0.187436  0.227500  0.218291  0.201937  0.212855  0.172500  \n",
       "4.0  0.199178  0.194200  0.166775  0.186650  0.200456  0.179150  0.193475  \n",
       "4.1  0.223700  0.198700  0.211793  0.210700  0.168300  0.200883  0.202600  \n",
       "4.2  0.143350  0.162450  0.185694  0.196530  0.181363  0.124100  0.154300  \n",
       "4.3  0.177400  0.182486  0.168967  0.240900  0.198540  0.211260  0.154700  \n",
       "4.4  0.193763  0.180425  0.098260  0.176700  0.130213  0.205100  0.233800  \n",
       "4.5  0.238050  0.184175  0.165300  0.247133  0.185775  0.235250  0.209500  \n",
       "4.6  0.185767  0.120300  0.137700  0.137350  0.183275  0.197100  0.000000  \n",
       "4.7  0.237600  0.190820  0.058800  0.225250  0.261800  0.103200  0.075550  \n",
       "4.8  0.265200  0.163650  0.075500  0.108400  0.202933  0.067500  0.000000  \n",
       "4.9  0.135033  0.195800  0.000000  0.082100  0.072100  0.078550  0.000000  \n",
       "5.0  0.030700  0.000000  0.000000  0.000000  0.084400  0.070900  0.000000  \n",
       "\n",
       "[36 rows x 181 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_pivoted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.heatmap(\n",
    "    df_pivoted,\n",
    "    robust=True,\n",
    "    square=False,\n",
    "    cmap=colormaps[\"rainbow\"],\n",
    "    xticklabels=False,\n",
    "    yticklabels=False,\n",
    "    vmax=0.8,\n",
    ")\n",
    "ax.set_yticks([5, 15, 25, 35], [2, 3, 4, 5])\n",
    "ax.set_xticks([39, 89, 139], [-100, 0, 100])\n",
    "# ax.set_xticks([79, 179, 279], [-100, 0, 100])\n",
    "ax.set_xlabel(f\"$\\phi$ [deg]\")\n",
    "ax.set_ylabel(f\"$\\eta$\")\n",
    "\n",
    "# ax.set_yticklabels([])\n",
    "ax.invert_yaxis()\n",
    "ax.set_title(\"LHCb VELO $x/X_0$\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "tuner",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}